class_docstr: Computes the standard deviation for each metric from samples.
class_docstr_tok: ["Computes","the","standard","deviation","for","each","metric","from","samples","."]
code: def extract_output(
      self, accumulator: "SampleCombineFn.SampleAccumulator"
  ) -> metric_types.MetricsDict:
      raise NotImplementedError("Must be implemented in subclasses.")
  
file_path: model-analysis/tensorflow_model_analysis/evaluators/confidence_intervals_util.py
imports: import collections
  import numbers
  from typing import Iterable, NamedTuple, Optional, Sequence, Set, Tuple
  import apache_beam
  import numpy
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.post_export_metrics import metric_keys
label_desc: Use image node_id 6 for calling the SampleCombineFn obj's underlying member method code with example usage: obj.extract_output(accumulator) without return types